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ESSnet on the use of administrative and accounts data in business statistics

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ESSnet on the use of administrative and accounts data in business statistics Development of Quality Indicators (WP6) John-Mark Frost (ONS, UK), Humberto Pereira (INE ... – PowerPoint PPT presentation

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Title: ESSnet on the use of administrative and accounts data in business statistics


1
ESSnet on the use of administrative and accounts
data in business statistics Development of
Quality Indicators (WP6)
John-Mark Frost (ONS, UK), Humberto Pereira (INE,
PT), Sofia Rodrigues (INE, PT), Ana Chumbau (INE,
PT), Jorge Mendes (INE, PT) and Sarah Green
(ONS, UK), Q2010, 4th May 2010
2
Overview
  • Work package (WP) partners
  • Aims of the WP
  • Why this work is important
  • Work done so far
  • Next steps

3
WP partners



4
Aims of the WP (2009 2013)
  • To collect and analyse information on existing
    methods used in NSIs for quality assessment when
    administrative data are used.
  • To develop quantitative quality indicator(s) for
    business statistics produced using administrative
    data, and
  • To develop qualitative indicators to complement
    the quantitative one(s).

5
Why this work is important
  • Increasing use of administrative data in business
    statistics
  • Dimensions of quality apply but
  • - Quality reporting is not entirely the same
  • - CVs cannot be used when solely using
    administrative data
  • Best practice in other areas will depend on
    appropriate and effective measures of quality

6
Work done so far
  • Focussed on
  • collecting and analysing information on existing
    methods used in NSIs for quality assessment when
    administrative data are used.

7
Phase 1 Methodology
  • Developed Questionnaire
  • Use of administrative data in business statistics
  • Use of quality checks
  • Circulated to 34 NSIs
  • 27 Member States
  • 4 EFTA
  • 3 Non-European
  • 90 response rate

8
Phase 1 Results (1)
  • Administrative data used extensively in business
    statistics
  • Quality considered an important issue
  • Lots of generic checks conducted during the
    process of statistics production

9
Phase 1 Results (2)
  • But
  • checks are not necessarily formal and very few
    are published as quality indicators
  • only half the NSIs indicated that they produce
    any kind of quantitative quality measure

10
Phase 2 Methodology
  • Identified 16 NSIs that showed the most
    experience in the area of quality indicators
  • Sent more extensive questionnaires, specifically
    asking about quantitative quality indicators in
    the areas of SBS, STS, Business Registers and
    Prodcom
  • 100 response rate

11
Phase 2 Results
  • Consistent with Phase 1
  • NSIs check quality
  • Checks are generally made as part of the
    statistical production process
  • But the checks are not necessarily produced on
    a regular or formal basis.

12
Phase 3 Methodology
  • Identified 7 more experienced NSIs and
    requested to meet with them
  • Engaged in face-to-face interviews with relevant
    staff within the NSIs to
  • - Better understand their use of administrative
    data in business statistics
  • - Gain clarity on their responses in Phase 2
  • Get more detailed information on their use of
    quality indicators

13
Phase 3 Results (1)
  • NSIs engaged in similar quality checks
  • Accuracy
  • e.g. of units with correct activity code
  • Coverage
  • e.g. comparison of units included in
    administrative source with units in the BR to
    estimate under / over-coverage
  • Missing data/non-response,
  • e.g. of turnover accumulated at publication of
    first estimate

14
Phase 3 Results (2)
  • Revisions
  • e.g. differences between first and final
    estimates
  • Matching (more relevant for NSIs without unique
    identifiers)
  • e.g. of matched units from both sources
  • Coefficients of Variation (when combining
    administrative and survey data)
  • e.g. using the jack-knife method
  • However, very few of these checks were produced
    as formal, quality indicators

15
Summary of work so far
  • Administrative data are widely used in business
    statistics
  • Quality is seen as important
  • Various checks are conducted during the
    statistical production process but
  • they are not necessarily formal or regular
  • they are rarely published
  • On the whole, NSIs do not produce quality
    indicators in the same way as when using survey
    data
  • Development of list of quality indicators
    welcomed by NSIs

16
The next steps
  • Build on the results of the stock-take research
  • Further develop the list of quality indicators
  • including user testing
  • Investigate composite quality indicators
  • Throughout, ensure that we
  • adopt a pragmatic approach
  • develop a user-friendly list of indicators
  • consider the limitations on NSIs (resource and
    data availability)

17
Some areas for consideration
  • Indicators that apply to both survey and
    administrative data
  • Not all NSIs will have access to the same level
    or type of information (either administrative or
    process related)
  • Qualitative as well as quantitative indicators

18
Thank you for listening


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